This document gives a few suggestions to analyse a dataset composed by a set of geographic coordinates that have an associated numeric value.

It considers the population of 925 cities in the UK. This example dataset is provided in the R maps library and is available on this Github repository. Basically it looks like the table beside.

# Libraries
library(tidyverse)
library(hrbrthemes)
library(kableExtra)
options(knitr.table.format = "html")
library(viridis)

# Load dataset from github
data <- read.table("https://raw.githubusercontent.com/holtzy/data_to_viz/master/Example_dataset/18_ListGPSCoordinatesWithValue.csv", header=T)

# show data
data %>% head(5) %>% kable() %>%
  kable_styling(bootstrap_options = "striped", full_width = F)

lat	long	pop	name
51.65	-3.14	10146	Abercarn-Newbridge
51.72	-3.46	33048	Aberdare
57.15	-2.10	184031	Aberdeen
51.83	-3.02	14251	Abergavenny
53.28	-3.58	17819	Abergele

1 Bubble map

# Get the world polygon and extract UK
library(maps)
UK <- map_data("world") %>% filter(region=="UK")

# Easy to make it interactive!
library(plotly)
 
# plot
p=data %>%
  
  arrange(pop) %>%
  mutate( name=factor(name, unique(name))) %>%
  mutate( mytext=paste("City: ", name, "\n", "Population: ", pop, sep="")) %>%  # This prepare the text displayed on hover.
 
  # Makte the static plot calling this text:
  ggplot() +
    geom_polygon(data = UK, aes(x=long, y = lat, group = group), fill="grey", alpha=0.3) +
    geom_point(aes(x=long, y=lat, size=pop, color=pop, text=mytext, alpha=pop) ) +
    
    scale_size_continuous(range=c(1,15)) +
    scale_color_viridis(option="inferno", trans="log" ) +
    scale_alpha_continuous(trans="log") +
    theme_void() +
    ylim(50,59) +
    coord_map() +
    theme(legend.position = "none")
 
ggplotly(p, tooltip="text")

A work by Yan Holtz for data-to-viz.com